I’m glad you’ve joined us again for our series on unpacking the new and improved 5th Edition Standards, Appendix 14. In today’s blog we examine the requirements of Appendix 14C and how you may respond clearly and succinctly in your SSR.
Appendix 14C requires data on the effectiveness of a program’s didactic curriculum. Your data should include student evaluations of their didactic courses and instructors, the number of final didactic course grades at “C” or below, and the attrition and remediation in didactic courses.
When graphing student evaluations, we list all didactic courses by their name and number. We identify faculty by the abbreviations found in the glossary (MD for Medical Director, PD for Program Director), then numerically. So, your Principal Faculty Members (glossary term PF) would be numbered as PF-1, PF-2, and so on.
You must present data in a way that allows comparison across courses for faculty who teach multiple classes, and which allows appreciation for trends over time.
Present quantitative data in aggregate, in tables/graphs that support the analysis directly.
Present quantitative data in “themes,” summarized in the narrative or displayed in an appended document. Quantitative data must also support the narrative. You select the themes of your quantitative data. Provided they are reasonable and sensible, the commission will accept them.
The following Chart A shows a way to line the data up in one graph. The data shows course ratings over a period of about five years, then combines it with thematic elements noted in qualitative data.
Chart B below displays the number of C-or-below grades in particular classes, then Chart C relates a student’s number of C-grades to their various other course work. This gives us the ability to see, based on C-grades, all the way to the PANCE. We can surmise from the chart that an increase in C-grades relates to a decline in PANCE performance.
The ARC-PA defines remediation as the program-defined and applied process for addressing deficiencies in a student’s knowledge and skills, such that the correction of these deficiencies is measurable and documentable.
Data to measure:
Chart D displays a simple total of remediations offered to members of a cohort.
Using parametric analysis to enhance assessment. The Commission Is not clear on how much, and when, you should do this. However, they use the term “correlation” many times in their literature, so in my estimation, correlating performances are important. They open a new layer of assessment that can help you to look at this information.
In Chart E, I share an example of an analysis of variance conducted on C-grades received and PANCE performance.
If you would like to know more about conducting regression studies on your student outcomes, I discuss the use of parametric analysis in depth in Massey Martin, LLC’s free online seminar series on the ARC-PA’s 5th Edition Standards. I invite you to attend and ask questions.
In our next blog post, we’ll continue with the 5th Edition Standards by discussing Appendix 14D.